Robust surveillance and control of invasive species using a scenario optimization approach

Uncertainty about future outcomes of invasions is a major hurdle in the planning of invasive species management programs. We present a scenario optimization model that incorporates uncertainty about the spread of an invasive species and allocates survey and eradication measures to minimize the number of infested or potentially infested host plants on the landscape. We demonstrate the approach by allocating surveys outside the quarantine area established following the discovery of the Asian longhorned beetle (ALB) in the Greater Toronto Area (GTA), Ontario, Canada. We use historical data on ALB spread to generate a set of invasion scenarios that characterizes the uncertainty of the pest's extent in the GTA. We then use these scenarios to find allocations of surveys and tree removals aimed at managing the spread of the pest in the GTA. It is optimal to spend approximately one-fifth of the budget on surveys and the rest on tree removal. Optimal solutions do not always select sites with the greatest propagule pressure, but in some cases focus on sites with moderate likelihoods of ALB arrival and low host densities. Our approach is generalizable and helps support decisions regarding control of invasive species when knowledge about a species' spread is uncertain.

[1]  Jean J Turgeon,et al.  Managing invasive populations of Asian longhorned beetle and citrus longhorned beetle: a worldwide perspective. , 2010, Annual review of entomology.

[2]  Jamie K. Reaser,et al.  Bioinvasions, bioterrorism, and biosecurity , 2003 .

[3]  Trond Rafoss,et al.  Spatial Stochastic Simulation Offers Potential as a Quantitative Method for Pest Risk Analysis , 2003, Risk analysis : an official publication of the Society for Risk Analysis.

[4]  Petr Pyšek,et al.  Invasive Species, Environmental Change and Management, and Health , 2010 .

[5]  D. Yemshanov,et al.  There is no silver bullet: The value of diversification in planning invasive species surveillance , 2014 .

[6]  G. Rasool,et al.  ANALYSIS OF GENETIC DIVERSITY IN , 2008 .

[7]  David P. Morton,et al.  Monte Carlo bounding techniques for determining solution quality in stochastic programs , 1999, Oper. Res. Lett..

[8]  R. Trotter,et al.  Quantifying Dispersal of the Asian longhorned beetle (Anoplophora glabripennis, Coleoptera) with incomplete data and behavioral knowledge , 2015, Biological Invasions.

[9]  O. Cacho,et al.  Optimization of Search Strategies in Managing Biological Invasions: A Simulation Approach , 2012 .

[10]  King Abdulaziz,et al.  Managing invasive populations of red palm weevil: A worldwide perspective , 2013 .

[11]  H. Mooney,et al.  Invasive species, ecosystem services and human well-being. , 2009, Trends in ecology & evolution.

[12]  James A. Turner,et al.  Designing cost-efficient surveillance strategies for early detection of invasive species , 2013 .

[13]  M. Mescher,et al.  Development and Evaluation of a Trapping System for Anoplophora glabripennis (Coleoptera: Cerambycidae) in the United States , 2014, Environmental entomology.

[14]  L R Carrasco,et al.  Optimal and robust control of invasive alien species spreading in homogeneous landscapes , 2010, Journal of The Royal Society Interface.

[15]  Ruitong Gao,et al.  Dispersal and Spatiotemporal Dynamics of Asian Longhorned Beetle (Coleoptera: Cerambycidae) in China , 2004 .

[16]  Rebecca S Epanchin-Niell,et al.  Designing cost-efficient surveillance for early detection and control of multiple biological invaders. , 2014, Ecological applications : a publication of the Ecological Society of America.

[17]  Andrew M. Liebhold,et al.  To sample or eradicate? A cost minimization model for monitoring and managing an invasive species , 2008 .

[18]  N. Straw,et al.  Host plant selection and resource utilisation by Asian longhorn beetle Anoplophora glabripennis (Coleoptera: Cerambycidae) in southern England , 2015 .

[19]  K. Hoover,et al.  Asian longhorned beetle (Coleoptera: Cerambycidae), an introduced pest of maple and other hardwood trees in North America and Europe , 2015 .

[20]  Andrew J. Mason,et al.  SolverStudio: A New Tool for Better Optimisation and Simulation Modelling in Excel , 2013, INFORMS Trans. Educ..

[21]  A Gerodimos,et al.  Robust Discrete Optimization and its Applications , 1996, J. Oper. Res. Soc..

[22]  C. Jucker,et al.  First record of Anoplophora glabripennis (Motschulsky) (Coleoptera Cerambycidae Lamiinae Lamiini) in Italy. , 2007 .

[23]  P. Groot,et al.  Asian Longhorned Beetle Anoplophora glabripennis (Motschulsky): Lessons Learned and Opportunites to Improve the Process of Eradication and Management , 2009 .

[24]  Denys Yemshanov,et al.  Mapping Invasive Species Risks with Stochastic Models: A Cross‐Border United States‐Canada Application for Sirex noctilio Fabricius , 2009, Risk analysis : an official publication of the Society for Risk Analysis.

[25]  Susan Hester,et al.  Allocating surveillance effort in the management of invasive species: A spatially-explicit model , 2010, Environ. Model. Softw..

[26]  B. Rustem,et al.  Simulation and optimization approaches to scenario tree generation , 2004 .

[27]  H. Ravn,et al.  Spatial spread and infestation risk assessment in the Asian longhorned beetle, Anoplophora glabripennis , 2015 .

[28]  Andrew M. Liebhold,et al.  Optimal surveillance and eradication of invasive species in heterogeneous landscapes. , 2012, Ecology letters.

[29]  L. Meyerson,et al.  Saving camels from straws: how propagule pressure-based prevention policies can reduce the risk of biological invasion , 2008, Biological Invasions.

[30]  Santanu Roy,et al.  On Prevention and Control of an Uncertain Biological Invasion , 2005 .

[31]  Robert G. Haight,et al.  Optimal strategies for the surveillance and control of forest pathogens: A case study with oak wilt , 2013 .

[32]  D. Finnoff,et al.  When is a “wait and see” approach to invasive species justified? , 2013 .

[33]  David W. Williams,et al.  Distribution and Abundance of Anoplophora glabripennis (Coleoptera: Cerambycidae) in Natural Acer Stands in South Korea , 2004 .

[34]  Mark Williamson,et al.  How to manage biological invasions under globalization. , 2005, Trends in ecology & evolution.

[35]  A. Hastings,et al.  Controlling established invaders: integrating economics and spread dynamics to determine optimal management. , 2010, Ecology letters.

[36]  Denys Yemshanov,et al.  Evaluating Critical Uncertainty Thresholds in a Spatial Model of Forest Pest Invasion Risk , 2009, Risk analysis : an official publication of the Society for Risk Analysis.

[37]  Robert G. Haight,et al.  Optimal control of an invasive species with imperfect information about the level of infestation , 2010 .

[38]  Constantine Caramanis,et al.  Theory and Applications of Robust Optimization , 2010, SIAM Rev..

[39]  V. Mastro,et al.  New York's battle with the Asian long-horned beetle , 1997 .

[40]  Peter Whittle,et al.  Info-gap theory and robust design of surveillance for invasive species: the case study of Barrow Island. , 2009, Journal of environmental management.

[41]  G. Smiatek,et al.  Land Use Data , 1997 .

[42]  John H. Pedlar,et al.  Density and Location of Simulated Signs of Injury Affect Efficacy of Ground Surveys for Asian Longhorned Beetle , 2010, The Canadian Entomologist.

[43]  Yelena Ogneva-Himmelberger,et al.  Characterizing the potential distribution of the invasive Asian longhorned beetle (Anoplophora glabripennis) in Worcester County, Massachusetts , 2013 .

[44]  P. Tobin.  Cost analysis and biological ramifications for implementing the gypsy moth Slow the Spread Program , 2008 .

[45]  E. Hoebeke,et al.  Revision of the genus Anoplophora (Coleoptera: Cerambycidae). , 2002 .

[46]  Shefali V. Mehta,et al.  Optimal detection and control strategies for invasive species management , 2007 .

[47]  R. Sequeira,et al.  Potential Effect of Anoplophora glabripennis (Coleoptera: Cerambycidae) on Urban Trees in the United States , 2001, Journal of economic entomology.

[48]  Guohong Li,et al.  Dispersal of Anoplophora glabripennis (Cerambycidae) , 2001 .

[49]  Robert G. Haight,et al.  Economic Impacts of Non-Native Forest Insects in the Continental United States , 2011, PloS one.

[50]  R. Scachetti-Pereira,et al.  Potential Geographic Distribution of Anoplophora glabripennis (Coleoptera: Cerambycidae) in North America , 2004 .

[51]  Wolfgang Nentwig,et al.  Grasping at the routes of biological invasions: a framework for integrating pathways into policy , 2008 .

[52]  Mark E. Eiswerth,et al.  Prevention or Control: Optimal Government Policies for Invasive Species Management , 2006, Agricultural and Resource Economics Review.

[53]  Andrew M. Liebhold,et al.  Benefits of invasion prevention: Effect of time lags, spread rates, and damage persistence , 2015 .

[54]  J. Mulvey.  Generating Scenarios for the Towers Perrin Investment System , 1996 .

[55]  M. Carter,et al.  Analysis of Genetic Diversity in an Invasive Population of Asian Long-Horned Beetles in Ontario, Canada , 2009, The Canadian Entomologist.

[56]  Brett A. Melbourne,et al.  Highly Variable Spread Rates in Replicated Biological Invasions: Fundamental Limits to Predictability , 2009, Science.

[57]  Robert G. Haight,et al.  Deploying initial attack resources for wildfire suppression: spatial coordination, budget constraints, and capacity constraints , 2013 .

[58]  Cindy E. Hauser,et al.  Streamlining 'search and destroy': cost-effective surveillance for invasive species management. , 2009, Ecology letters.